Description

Utilizing raw data from Bwin Interactive Entertainment, AG, an internet betting service provider, this project aims to extract marketing insights by analyzing customer data encompassing various products/services like sports betting, poker, and casino games. The data includes summary statistics and detailed descriptions of gambling metrics retrieved from a longitudinal study conducted between February 1, 2005, and September 30, 2005. This study includes demographics, daily betting aggregations, and poker chip conversion datasets, providing a comprehensive view of user behavior during this period. The objective is to construct a Marketing datamart delineating key variables and metrics per user, visualizing these insights through a Shiny Application.

Key Marketing Metrics

Customer Tenure denotes the Customer Tenure = closingDate - RegDate

FrequencyBetting = TotalBets / CustomerTenure

TransactionTypeRatio = NumberofBuyTrans / NumberofSellTrans

Net Profit = TotalWinnings - TotalStakes

WinRateBets = (TotalWinnings / TotalBets) * 100

WinRateStakes = (TotalWinnings / TotalStakes) * 100

AvgWinBets = TotalWinnings / TotalBets

AvgWinStakes = TotalWinnings / TotalStakes

Return on Investment = ((TotalWinnings - TotalStakes) / TotalStakes) * 100

CustomerLifetimeValue = TotalWinnings - TotalStakes

AverageSellTransValuePerCustomer = TotalTransAmountSell / NumberofSellTrans

AverageBuyTransValuePerCustomer = TotalTransAmountBuy / NumberofBuyTrans

CustomerActivityScore = (FrequencyBetting + FrequencyTransactions) / 2

CustEngagementScore = (numberBets/customerTenure)*100)

CustEngagementIndex = (CustEngagementScore+FrequencyBetting+FrequencyTransactions)/3

Loyalty = (TotalWinnings - TotalStakes) / (CustomerTenure * FrequencyBetting)

Gender Distribution

A major proportion of users are male with 39059 of the users being men and 3588 being women.

AvgWinBets based on Application Description

Applications with the highest Average Win Bets 1. Betandwin Poker 2. Betandwin.com 3. Balls of Fire 4. Betoto.com 5. BetEurope.com

AvgWinStakes based on Application Description

Applications with the highest Average Win Stakes 1. Betandwin.com 2. Betandwin Poker 3. BetEurope.com 4. Betoto.com 5. Balls of Fire

Customer Activity Score

Average Buy and Sell Transaction Value per Customer vs. First Active Date

The graph reveals a positive correlation between customer tenure and average buy and sell transaction values. This indicates that long-standing poker players are more inclined to engage in substantial stakes. This trend could be attributed to factors like familiarity, trust, and reputation. Experienced players are more confident in the platform’s reliability and may perceive larger stakes as opportunities to gain an edge. Their established position in the poker community often translates into larger bets.

Total Customer Tenure for Top 10 Countries

The above graph gives the total customer tenure for top 10 countries. The customers with the highest tenure are from Germany whereas the Swiss have the lowest tenure

## Selecting by TotalCustomerTenure
## Selecting by TotalCustomerTenure

Average Frequency Betting for Top 10 Countries

This stacked bar chart shows how the top 10 countries differ in their preference for specific types of betting applications. It visualizes the categories of applications that are popular in each country, allowing us to see trends in app usage patterns and identify potential opportunities for marketing.

## Selecting by AverageFrequencyBetting

Stacked Bar Plot of Application Descriptions for Top 10 Countries

This plot depicts the prevalence of apps utilized by individuals in the top 10 nations based on application category. The stacked bar provides insights into the distribution of distinct categories of apps across the top 10 nations. This plot can be used to recognize patterns in application usage across distinct nations and to identify potential opportunities for advertising and product development.

## Selecting by TotalApplications
## `summarise()` has grouped output by 'Country_Name'. You can override using the
## `.groups` argument.